Using GIS to Determine Goodness of Fit for Functional Classification. Eric Foster NWMSU MoDOT

Transcription

1 Using GIS to Determine Goodness of Fit for Functional Classification Eric Foster NWMSU MoDOT

2 Northwest Missouri State Masters of GIScience Degree Program University All Online Coursework

3 Missouri Department of District Transportation Planning KC Area Transportation Functional Classificattion Map Production Data Verification District Data Admin

4 Highway Functional Classification and GIS Purpose of the paper Satisfy Thesis Requirements for Degree Program Study Functional Class System Showcase Potential Use for GIS at DOT level

5 Using GIS to Determine Goodness of Fit of Functional Classification Objectives (1)Do currently approved functional classifications in the study area represent the functional classification derived using actual design criteria in the field? (2)Do currently approved functional classifications in the study area represent functional classifications as derived from planning data?

6 Overview of Process Study Area - Kansas City UZA Literature Review Used GIS to geographically sample Performed Statistical Testing Interpreted Results Conclusions KC UZA MO

7 Definition of Terms Average Annual Daily Traffic (AADT) an average of the daily traffic volume for a given Vehicle Miles Traveled (VMT) a unit of measure that calculates the total miles traveled by all vehicles in a specified area for a specific period of time.

8 Background and Key Concepts Various classification systems Interstate System STRAHNET (Strategic Highway Network) State System (Missouri Primary, Supplementary statutory system) NHS (National Highway System) Congressional High Priority Routes Major and Minor Highways (MoDOT implemented to aid in prioritizing construction and maintenance, loosely based on functional classification system Functional Classification

9 What is Functional Classification? Balance of Mobility and Access Mobility and Access Inversely Related Data of Ranked Scale

10 National vs. Local Functional Classification Systems FHWA APWA Focus on Highways Three main classes Arterials Collectors Local Roads Based on trip length, VMT, capacity, control of access Focus on non-highways Multiple classes at lower levels More classes at lower rank than FHWA system Based more on traffic volumes, sedondarily trip length, also access control

11 FHWA Functional Classification Arterials High mobility, Low access, Long trips, most VMT Principal arterials Interstates Freeways/Expressways Other principal arterials Minor arterials Collectors More mobility/less access than local roads Local Roads provide unlimited access, little mobility

12 KC Chapter APWA Functional Classes Major Arterial Streets Minor Arterial Streets Industrial/Commercial Collector Residential Collector Streets Residential Local Streets Residential Access Streets

13 Crosswalk for this study

14 Potential for Functional Classification Renew emphasis on procedures and objective guidelines Add efficiency to planning Help decision-makers More consideration of land use

15 Reasons for Further Developing Functional Classification System Has become a tool to merely secure funding Class breaks not exhaustively defined Fuzzy overlap between classes Trend toward less objectivity Linked to many DOT processes

16 Significance Further GIS use in DOTs Improved GIS Integration Show analysis power of GIS Help bring GIS to mainstream DOT practitioner Improved modeling of our environment

17 Significance Highlight GIS potential to reduce ambiguous and inaccurate data in DOT and Geography

18 Study Area Urbanized Area for Kansas City FHWA Smoothed Urbanized Area Traffic Generators Sprint and Hallmark Kansas Speedway Int l Airport Strong Parkway and Blvd system No light rail Typical grid/radial layout

19 Literature Review Historical Development Published Studies Other Classification Systems Data and Definition Issues HPMS

20 Historical Development of Functional Classification definition of traffic capacity AASHO Policies on Geometric Highway Design 1950 to 1964, no references to specific development of functional classification system 1964 First published mention of the functional classification 1964 Technical procedures 1967 Functional Classification in Missouri (MSHD) and other States 1969, 1970, 1976, and 1989 FHWA, USDOT, AASHTO 1989 Functional Classification Guidelines: Concepts, Criteria, and Procedures

21 Other Countries Classification Systems Canada s functional classification system is similar to that in the U.S. for urban areas More industrial economy Higher truck % than U.S.

22 Other Countries Classification Systems Germany s classification system (Garrick and Kuhnimhof 2000) Authorities overlook the importance of FC Considers surrounding land use Non-vehicular uses of streets Nearness to built-up areas Whether buildings surround the route Whether the street serves as a pedestrian gathering place

23 Review of Definitions Access and Mobility not just about travel Access and Mobility in terms of rights and privileges Ambiguous Class Definition FHWA Guidelines (FHWA 1989) do not adequately define objective class breaks Allows subjective judgment from state to state and region to region

24 Pisarski (1999) Data Considerations We are more and more capable of rapidly transferring and effectively manipulating less and less accurate information Accuracy of Linear Referencing Traffic Volume Estimation Issues Estimating Origin-Destination (O-D) data

25 Functional Class and HPMS Highway Performance Monitoring System Sampling Error Bias in practice

26 What is HPMS? Data collection program Uses Allocation of Federal Funds to the States. Federal and State policies. Bureau of Transportation Statistics EPA air quality conformity tracking

27 HPMS Sample Design Issues Functional Class as HPMS stratifier Confidence levels and values for sample size No mention the potential error of misclassification Discusses samples that change in classification over time and the handling of them No guidance on determining error or correctness within a class

28 Bias in HPMS Inconsistent procedures by various state DOTs Timing of data collection Subjective bias Terminology appropriate classification criteria good engineering judgment Loss of normalization across classes and geographic areas Different state interpretation of definitions Application of percentage ranges on different types of geographies

29 HPMS Remedies in Draft Report Eliminate area designation as a stratifier Update Guidance Training Develop functional classes for non-centerline facilities Ramps one-way connectors Functional system seems to be a poor choice as a stratifier

30 Summary of Literature Review No recent advances in the definition of functional classification. Most literature reviewed contained evidence of support for my claim

31 Methodology ArcGIS 9.2 Data Model Buffer for Sampling Select by Attributes/Location to Sample Validate EMME/2 Samples with Road Centerlines Visual Match of segments Reassignment if necessary Calculate VMT Export to Spreadsheet for Statistics Add Measured Curve Data Run Statistics

32 Objectives Review (1) Do currently approved functional classifications in the study area represent the functional classification derived using actual design criteria in the field? (2) Do currently approved functional classifications in the study area represent functional classifications as derived from planning data?

33 Research Framework Measures of Transportation System Data and Sources Description of the GIS model Sampling Design Statistical Testing Limitations

34 Measures of the Transportation System Circulatory system in the human body Central arteries Veins Capillaries Functional classifications Aggregate of Basic Measures Traffic volume VMT Trip length Trip purpose Used to determine design criteria

35 Design Criteria Access control Design speed of the roadway Interchange, Intersection, Entrance, and Driveway Spacing Maximum Vertical Gradient Minimum Radius of Horizontal Curvature Minimum Sight Distance Minimum Slope Ratios Number of Lanes Pavement Design Pavement Edge Treatment Type of median Vertical curve sag value Width of the driving lane Width and Material Type

36 Horizontal Curvature Fundamental criterion related to design speed Ease of Measurement Objective data Degree of curvature (D) in decimal degrees Radius of curvature (R) in feet D / 360 = 100 / 2 Π R R = / D

37 Planning Data Trip Length, Travel Density, Land Use, Population, VMT AADT and VMT for study Widespread use Representative of travel demand more than other typical DOT data VMT derived from a travel demand model EMME/2 Schematic Model AADT Forecast to 2010

38 List of Data Sources Data Type Road Centerlines 2007 Aerial Photography FHWA Approved Functional Classifications 2000 KC UZA (FHWA) Horizontal Curve Radius AADT and VMT Source MoDOT and MARC NAIP 2007, MSDIS MoDOT MoDOT NAIP 2007, Microstation MARC EMME/2 Model

39 Stratified Sample Design Desire to spread samples Several cities and counties Different interpretations of functional classification Different travel character, population, development Network denser near CBD 4 Concentric Rings

40 Basis for Sample Segment No Best Basis Functional class is continuous Great distances or node-to-node EMME/2 straight-line segments EMME/2 data was not as spatially accurate as GIS Links represent more than single route Some links represented the total traffic assigned between two generators Segments treated as outlier and replaced Systematic Sample EMME/2 Functional Class did not match GIS Matched the segments visually in ArcMap

41 EMME/2 vs. GIS Segments

42 Samples with Functional Class Symbolization

43 Statistical Methodology Two Chi Square (X 2 ) Statistical Tests 1. Measured minimum radius of horizontal curve (observed) vs. MoDOT/APWA prescribed minimum radius of horizontal curvature (expected) 2. VMT derived from GIS length of segment and EMME/2 forecasted AADT (observed) vs. prescribed VMT determined by FHWA guidelines for VMT percentage ranges for the functional class system (expected)

44 Observed Horizontal Curve Radius Comparison As-built plans too time consuming GIS does not model curves well Measured using CAD Expected MoDOT Policy, Procedure, and Design Manual APWA Standard Specification and Design Criteria AASHTO Green Book

45 Typical Measurement of a Horizontal Curve in Microstation

46 Expected Values for Minimum Horizontal Radius of Curve

47 VMT Comparison Expected Total of all VMT in EMME/2 population applied by VMT ranges from FHWA guidelines Observed AADT X Length of EMME/2 segments

48 Observed VMT Calculated VMT using the EMME/2 forecasted AADT values and the Shape_Length field created by ArcMap Street centerline data was more spatially accurate than the EMME/2 segments, but no common field to join street centerline data with the EMME/2 data

49 Expected values for VMT FHWA Prescribed Ranges

50 VMT Conversion Principal Arterials Principal Arterials plus Minor Arterials Collectors Local Streets Principal Arterials Interstates Freeway/expressways Other principal arterials Minor Arterials Collectors Local Streets

51 Derived VMT Ranges

52 Application of Total VMT to EMME/2 Population

53 Test Hypotheses Horizontal Minimum Radius of Curve H 0 : The observed values of minimum horizontal curve radius are less than or equal to the expected values of minimum horizontal curve radius to a P-level of H a : The observed values of minimum horizontal curve radius are not less than or equal to the expected values of minimum horizontal curve radius to a P-level of 0.05.

54 Test Hypotheses Vehicle Miles Traveled H 0 : The observed values of VMT are within the range of expected values of minimum horizontal curve radius to a P-level of H a : The observed values of VMT are not within the range of the expected values of minimum horizontal curve radius to a P-level of 0.05.

55 Test Data 100 hundred samples, 20 from each of the functional classes included Spreadsheet Data Descriptive data about samples Calculated fields Observed values (Radius and VMT) Expected values (Radius and VMT) Conditional IF statement fields for Radius and VMT

56 Descriptive Data

57 Portion of Sampled Horizontal Curve Data

58 Portion of Sampled VMT Data

59 Limitations Evolution of design standards Error due to Design Exceptions Spatial variation of attribute values Differences in design criteria Technical error

60 Evolution of Design Standards Standards of transportation planning and design have not remained constant Design Exceptions Design Exceptions

61 Spatial Variation VMT, ADT, and trip data vary inversely with the distance to an urban core Negative spatial auto-correlation Design Standard Differences AASHTO vs. APWA Functional classification Design Criteria Difficult to prove that segments do not match Technical Error

62 EMME/2 Errors Incorrect Modeling of Functional Classes actual Interstates as freeway/expressway some Interstates as principal arterials Modeled some freeway/expressways as Interstates Modeled some freeway/expressways as principal arterials Model aggregation minor arterials and collectors as a single class Corrected during sampling Substitution with the geographically closest segment Ring deficiencies Exclude Local Roads Length Issues Logical Termini differences, different VMT values

63 Ambiguity Overlapping Class Breaks Principal Arterials, Minor Arterials both are prescribed to carry regional trips No objective definition of regional trip Lack of Objective Data ADT and subsequently VMT for the statistical testing are not all actual counts If I used only those, sample size unacceptable

64 Differences in Procedures Classification Procedures Subjective classification methods Application of VMT and mileage ranges Measurement of Error Difficult to quantify Corrections should be considered for further study None used for this study

65 Error Exists This fact alone supports my claim Need more definition and development of procedures regarding the Functional Class system

66 Analysis Results and Discussion Chi Square (c²) calculations Separate attempts to determine significant difference Perfect world expect 20 out of 20 to meet criteria Due to the potential and probable error, cannot truly expect that Cannot quantify error easily Used a 5% average error 19 of 20 meet expectations

67 Horizontal Curve Statistical Testing

68 VMT Statistical Testing

69 Interpretation of Results Horizontal Curve Radius No significant difference Null hypothesis was not rejected If we use horizontal curve radius alone to determine functional class, there is a 95% chance that the FHWA approved classes for the study area are correct For VMT, tests showed significant difference Null hypothesis can be rejected If we used VMT alone to determine functional class, it is likely that approved classification of segments are incorrect

70 Interpretation of Results Deeper look at Results Various categories (classes) have high (c²) statistical values Horizontal curve test principal arterial category had only half samples meet criteria Interstates also high There may be a significant amount of principal arterial segments with substandard curve radii in the study area population

71 Interpretation of Results VMT for collector class was very high High enough Chi Square (c²) value in this class alone to show significant difference for entire test Many collector segments in the study area might meet VMT thresholds for higher classes Difficult to determine or decide from this test that these classes are incorrect without further study Include other variables Allow for overlap of VMT in classes Does support, though, that there is ambiguity in at least VMT variable used in classification Lends support my call for further study of the functional classification system

72 Interpretation of Results No easy method to quantify the potential error Also ran the statistics using a 0% and a 10% error correction in the expected values No matter what was chosen as an error correction for the expected value, the results were fundamentally the same Test showed significant difference for VMT as a criteria for deriving rather than a criteria derived from functional class (Curve Radius)

73 Further Study Conflicting Results of separate tests Exclusion of more pertinent variables No clear answer Results do, however, support further study to help determine these answers Include more variables Quantify error correction More accurate measurement techniques Symbolization of rank order data Examination and quantification of the uses of functional classification

74 Conclusion

75 Summary There is need more study of the functional classification system Do we leave classification general and ambiguous yet tie it to so many of our crucial planning and design processes???

76 References ASSHTO FHWA/USDOT/Bureau of Public Roads KC Chapter of APWA MoDOT MSDIS US Census EPA Numerous Other Literature Available in Paper

77 Family Acknowledgments Supported me through coursework and thesis MoDOT MARC staff Provided data and expertise MOBIUS and Librarian Thesis committee

78 Contact Information (816) Questions???